Correlation between gene methylation status and clinical features

Lung Squamous Cell Carcinoma (Primary solid tumor)

17 October 2014 | analyses__2014_10_17

Maintainer Information

Citation Information

Maintained by Juok Cho (Broad Institute)

Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between gene methylation status and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1H41Q96

Overview

Introduction

This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.

Summary

Testing the association between 20228 genes and 14 clinical features across 288 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 4 clinical features related to at least one genes.

67 genes correlated to 'AGE'.

KIAA1143 , KIF15 , EML4 , CCDC13 , APOD , ...

16 genes correlated to 'GENDER'.

ALG11__2 , UTP14C , KIF4B , ATP5J , GABPA__1 , ...

446 genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.

KLHL9 , ZNF326 , PMS2L2 , STAG3L1__1 , DPY19L4 , ...

2 genes correlated to 'RACE'.

SCAMP5 , PM20D1

No genes correlated to 'Time to Death', 'NEOPLASM.DISEASESTAGE', 'PATHOLOGY.T.STAGE', 'PATHOLOGY.N.STAGE', 'PATHOLOGY.M.STAGE', 'HISTOLOGICAL.TYPE', 'RADIATIONS.RADIATION.REGIMENINDICATION', 'NUMBERPACKYEARSSMOKED', 'COMPLETENESS.OF.RESECTION', and 'ETHNICITY'.

Results

Overview of the results

Complete statistical result table is provided in Supplement Table 1

Table 1. Get Full Table This table shows the clinical features, statistical methods used, and the number of genes that are significantly associated with each clinical feature at P value < 0.05 and Q value < 0.3.

Clinical feature	Statistical test	Significant genes	Associated with		Associated with
Time to Death	Cox regression test	N=0
AGE	Spearman correlation test	N=67	older	N=4	younger	N=63
NEOPLASM DISEASESTAGE	Kruskal-Wallis test	N=0
PATHOLOGY T STAGE	Spearman correlation test	N=0
PATHOLOGY N STAGE	Spearman correlation test	N=0
PATHOLOGY M STAGE	Kruskal-Wallis test	N=0
GENDER	Wilcoxon test	N=16	male	N=16	female	N=0
KARNOFSKY PERFORMANCE SCORE	Spearman correlation test	N=446	higher score	N=409	lower score	N=37
HISTOLOGICAL TYPE	Kruskal-Wallis test	N=0
RADIATIONS RADIATION REGIMENINDICATION	Wilcoxon test	N=0
NUMBERPACKYEARSSMOKED	Spearman correlation test	N=0
COMPLETENESS OF RESECTION	Kruskal-Wallis test	N=0
RACE	Kruskal-Wallis test	N=2
ETHNICITY	Wilcoxon test	N=0

Clinical variable #1: 'Time to Death'

No gene related to 'Time to Death'.

Table S1. Basic characteristics of clinical feature: 'Time to Death'


Time to Death	Duration (Years)	1-5287 (median=492.5)
	censored	N = 189
	death	N = 71

	Significant markers	N = 0

Clinical variable #2: 'AGE'

67 genes related to 'AGE'.

Table S2. Basic characteristics of clinical feature: 'AGE'


AGE	Mean (SD)	67.58 (8.8)
	Significant markers	N = 67
	pos. correlated	4
	neg. correlated	63

List of top 10 genes differentially expressed by 'AGE'

Table S3. Get Full Table List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

	SpearmanCorr	corrP	Q
KIAA1143	0.3278	1.95e-08	0.000394
KIF15	0.3278	1.95e-08	0.000394
EML4	-0.3085	1.384e-07	0.0028
CCDC13	-0.3065	1.67e-07	0.00338
APOD	-0.3002	3.075e-07	0.00622
MS4A6A	-0.2964	4.382e-07	0.00886
KIAA0232	-0.2921	6.552e-07	0.0132
TSC22D4	-0.2908	7.338e-07	0.0148
VPS13D	-0.2849	1.251e-06	0.0253
SPRY1	-0.2845	1.296e-06	0.0262

Clinical variable #3: 'NEOPLASM.DISEASESTAGE'

No gene related to 'NEOPLASM.DISEASESTAGE'.

Table S4. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'


NEOPLASM.DISEASESTAGE	Labels	N
	STAGE I	2
	STAGE IA	57
	STAGE IB	82
	STAGE II	1
	STAGE IIA	47
	STAGE IIB	48
	STAGE IIIA	41
	STAGE IIIB	5
	STAGE IV	3

	Significant markers	N = 0

Clinical variable #4: 'PATHOLOGY.T.STAGE'

No gene related to 'PATHOLOGY.T.STAGE'.

Table S5. Basic characteristics of clinical feature: 'PATHOLOGY.T.STAGE'


PATHOLOGY.T.STAGE	Mean (SD)	1.93 (0.72)
		N
	1	76
	2	166
	3	37
	4	9

	Significant markers	N = 0

Clinical variable #5: 'PATHOLOGY.N.STAGE'

No gene related to 'PATHOLOGY.N.STAGE'.

Table S6. Basic characteristics of clinical feature: 'PATHOLOGY.N.STAGE'


PATHOLOGY.N.STAGE	Mean (SD)	0.45 (0.65)
		N
	0	179
	1	79
	2	24

	Significant markers	N = 0

Clinical variable #6: 'PATHOLOGY.M.STAGE'

No gene related to 'PATHOLOGY.M.STAGE'.

Table S7. Basic characteristics of clinical feature: 'PATHOLOGY.M.STAGE'


PATHOLOGY.M.STAGE	Labels	N
	M0	233
	M1	2
	M1A	1
	MX	50

	Significant markers	N = 0

Clinical variable #7: 'GENDER'

16 genes related to 'GENDER'.

Table S8. Basic characteristics of clinical feature: 'GENDER'


GENDER	Labels	N
	FEMALE	73
	MALE	215

	Significant markers	N = 16
	Higher in MALE	16
	Higher in FEMALE	0

List of top 10 genes differentially expressed by 'GENDER'

Table S9. Get Full Table List of top 10 genes differentially expressed by 'GENDER'. 0 significant gene(s) located in sex chromosomes is(are) filtered out.

	W(pos if higher in 'MALE')	wilcoxontestP	Q	AUC
ALG11__2	15074	6.793e-32	1.37e-27	0.9604
UTP14C	15074	6.793e-32	1.37e-27	0.9604
KIF4B	2105	9.678e-21	1.96e-16	0.8659
ATP5J	12544	2.203e-14	4.46e-10	0.7992
GABPA__1	12544	2.203e-14	4.46e-10	0.7992
DDX43	3823	5.944e-11	1.2e-06	0.7564
YARS2	3855	8.409e-11	1.7e-06	0.7544
C6ORF108	4241	4.484e-09	9.07e-05	0.7298
TMEM232	4341	1.18e-08	0.000239	0.7234
BMS1	4899	1.627e-06	0.0329	0.6879

Clinical variable #8: 'KARNOFSKY.PERFORMANCE.SCORE'

446 genes related to 'KARNOFSKY.PERFORMANCE.SCORE'.

Table S10. Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'


KARNOFSKY.PERFORMANCE.SCORE	Mean (SD)	60.86 (39)
	Significant markers	N = 446
	pos. correlated	409
	neg. correlated	37

List of top 10 genes differentially expressed by 'KARNOFSKY.PERFORMANCE.SCORE'

Table S11. Get Full Table List of top 10 genes significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

	SpearmanCorr	corrP	Q
KLHL9	0.66	5.157e-10	1.04e-05
ZNF326	-0.6485	1.279e-09	2.59e-05
PMS2L2	0.6294	5.347e-09	0.000108
STAG3L1__1	0.6294	5.347e-09	0.000108
DPY19L4	0.6261	6.78e-09	0.000137
NDUFB9__1	0.6257	6.956e-09	0.000141
TATDN1__1	0.6257	6.956e-09	0.000141
ZNF260	0.6208	9.851e-09	0.000199
ARF4	0.6207	9.901e-09	2e-04
RAB23	0.6171	1.279e-08	0.000259

Clinical variable #9: 'HISTOLOGICAL.TYPE'

No gene related to 'HISTOLOGICAL.TYPE'.

Table S12. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'


HISTOLOGICAL.TYPE	Labels	N
	LUNG BASALOID SQUAMOUS CELL CARCINOMA	9
	LUNG PAPILLARY SQUAMOUS CELL CARICNOMA	5
	LUNG SMALL CELL SQUAMOUS CELL CARCINOMA	1
	LUNG SQUAMOUS CELL CARCINOMA- NOT OTHERWISE SPECIFIED (NOS)	273

	Significant markers	N = 0

Clinical variable #10: 'RADIATIONS.RADIATION.REGIMENINDICATION'

No gene related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S13. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'


RADIATIONS.RADIATION.REGIMENINDICATION	Labels	N
	NO	11
	YES	277

	Significant markers	N = 0

Clinical variable #11: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

Table S14. Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'


NUMBERPACKYEARSSMOKED	Mean (SD)	52.19 (30)
	Significant markers	N = 0

Clinical variable #12: 'COMPLETENESS.OF.RESECTION'

No gene related to 'COMPLETENESS.OF.RESECTION'.

Table S15. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'


COMPLETENESS.OF.RESECTION	Labels	N
	R0	222
	R1	5
	R2	2
	RX	13

	Significant markers	N = 0

Clinical variable #13: 'RACE'

2 genes related to 'RACE'.

Table S16. Basic characteristics of clinical feature: 'RACE'


RACE	Labels	N
	ASIAN	7
	BLACK OR AFRICAN AMERICAN	10
	WHITE	224

	Significant markers	N = 2

List of 2 genes differentially expressed by 'RACE'

Table S17. Get Full Table List of 2 genes differentially expressed by 'RACE'

	ANOVA_P	Q
SCAMP5	7.348e-07	0.0149
PM20D1	5.913e-06	0.12

Clinical variable #14: 'ETHNICITY'

No gene related to 'ETHNICITY'.

Table S18. Basic characteristics of clinical feature: 'ETHNICITY'


ETHNICITY	Labels	N
	HISPANIC OR LATINO	6
	NOT HISPANIC OR LATINO	189

	Significant markers	N = 0

Methods & Data

Input

Expresson data file = LUSC-TP.meth.by_min_clin_corr.data.txt
Clinical data file = LUSC-TP.merged_data.txt
Number of patients = 288
Number of genes = 20228
Number of clinical features = 14

Survival analysis

For survival clinical features, Wald's test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values using the 'coxph' function in R. Kaplan-Meier survival curves were plot using the four quartile subgroups of patients based on expression levels

Correlation analysis

For continuous numerical clinical features, Spearman's rank correlation coefficients (Spearman 1904) and two-tailed P values were estimated using 'cor.test' function in R

ANOVA analysis

For multi-class clinical features (ordinal or nominal), one-way analysis of variance (Howell 2002) was applied to compare the log2-expression levels between different clinical classes using 'anova' function in R

Student's t-test analysis

For two-class clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2-expression levels between the two clinical classes using 't.test' function in R

Q value calculation

For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.

Download Results

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

References

[1] Andersen and Gill, Cox's regression model for counting processes, a large sample study, Annals of Statistics 10(4):1100-1120 (1982)

[2] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)

[3] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)

[4] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)

[5] Benjamini and Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, Journal of the Royal Statistical Society Series B 59:289-300 (1995)

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